Forecasting NBA basketball playoff outcomes using the weighted likelihood
Why this work is in the frame
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Bibliographic record
Abstract
<!-- *** Custom HTML *** --> Predicting the outcome of a future game between two sports teams poses a challenging problem of interest to statistical scientists as well as the general public. To be effective such prediction must exploit special contextual features of the game. In this paper, we confront three such features and address the need to: (i) use all relevant sample information; (ii) reflect the home court advantage. To do so we use the relevance weighted likelihood of Hu and Zidek (2002). Finally we demonstrate the value of the method by showing how it could have been used to predict the 1996–1997 NBA Final series results. Our relevance likelihood-based method proves to be quite accurate.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it